CN111739018B - Chromatic aberration detection method, device, terminal and medium based on point cloud technology - Google Patents
Chromatic aberration detection method, device, terminal and medium based on point cloud technology Download PDFInfo
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- G06T7/0002—Inspection of images, e.g. flaw detection
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Abstract
The application is applicable to the technical field of image processing, and provides a color difference detection method, a device, a terminal and a medium based on a point cloud technology, wherein the color difference detection method comprises the following steps: acquiring first point cloud data of the surface of a building; restoring a first point cloud image of the building surface according to the first point cloud data; and acquiring a preset standard color block, and performing color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result. The embodiment of the application improves the efficiency, reliability and traceability of chromatic aberration detection.
Description
Technical Field
The application belongs to the technical field of image processing, and particularly relates to a color difference detection method, a color difference detection device, a color difference detection terminal and a color difference detection medium based on a point cloud technology.
Background
In the construction industry, people often make demands on the color of the architectural surface of the decorative surface. For example, it is desirable that fair-faced concrete panels do not provide a building surface that varies too much in color from area to area.
However, at present, the color difference detection of the building surface can only be recognized and checked by naked eyes, is influenced by individual subjectivity, has low detection efficiency and poor reliability, is not easy to trace, and needs a reliable building surface color difference detection method.
Disclosure of Invention
The embodiment of the application provides a color difference detection method, a color difference detection device, a terminal and a medium based on a point cloud technology, and can solve the problems that in the prior art, the color difference detection is poor in reliability and low in efficiency and is difficult to trace.
A first aspect of an embodiment of the present application provides a color difference detection method based on a point cloud technology, where the method includes:
acquiring first point cloud data of the surface of a building;
restoring a first point cloud image of the building surface according to the first point cloud data;
and acquiring a preset standard color block, and performing color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result.
A second aspect of the embodiments of the present application provides a color difference detection apparatus based on a point cloud technology, the apparatus includes:
the data acquisition unit is used for acquiring first point cloud data of the surface of the building;
the data processing unit is used for restoring a first point cloud image of the building surface according to the first point cloud data;
and the color difference detection unit is used for acquiring a preset standard color block and carrying out color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result.
A third aspect of the embodiments of the present application provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method when executing the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the above method.
A fifth aspect of embodiments of the present application provides a computer program product, which when run on a terminal device, causes the terminal device to perform the steps of the method.
In the embodiment of the application, the first point cloud image of the building surface is restored by acquiring the first point cloud data of the building surface and according to the first point cloud data. At this time, a preset standard color block may be obtained, and the first cloud image is subjected to color difference detection by using the standard color block, so as to obtain a first color difference detection result. The embodiment of the application realizes the color difference detection of the building surface, and the color difference detection result is obtained by comparing the color difference of the first point cloud image with the preset standard color block instead of judging the color difference through human eyes, so that the influence of individual subjectivity is avoided, the reliability and traceability of the color difference detection result are improved, and the efficiency is higher compared with the existing artificial color difference detection mode.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a first implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present application;
fig. 2 is a schematic flow chart of an implementation of image segmentation on a first point cloud image according to an embodiment of the present disclosure;
FIG. 3 is a first schematic view of an architectural surface provided by an embodiment of the present application;
fig. 4 is a schematic flowchart of a second implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present disclosure;
fig. 5 is a schematic flow chart of a third implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present application;
fig. 6 is a schematic flow chart of a fourth implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present application;
FIG. 7 is a second schematic view of an architectural surface provided by an embodiment of the present application;
fig. 8 is a schematic flowchart of a fifth implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of a color difference detection apparatus based on a point cloud technology according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a terminal according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In the construction industry, people often require the color of architectural surfaces (e.g., windows, doors, walls) with decorative surfaces. For example, it is desirable that fair-faced concrete panels do not provide a building surface that varies too much in color from area to area.
However, at present, the color difference detection of the building surface can only be recognized and checked by naked eyes, is influenced by individual subjectivity, has low detection efficiency and poor reliability, is not easy to trace, and needs a reliable building surface color difference detection method.
Based on this, embodiments of the present application provide a color difference detection method, apparatus, terminal and computer-readable storage medium based on a point cloud technology, which can solve the problems in the prior art that the color difference detection reliability is low and is not easy to be traced.
In order to explain the technical means of the present application, the following description will be given by way of specific examples.
Fig. 1 shows a schematic flow chart of a first implementation of a color difference detection method based on a point cloud technology according to an embodiment of the present application, where the method may be applied to a terminal, may be executed by a color difference detection apparatus based on a point cloud technology configured on the terminal, and is suitable for a situation where reliability of the color difference detection method needs to be improved.
Specifically, the color difference detection method based on the point cloud technology may include the following steps 101 to 103.
The first point cloud data refers to a point data set obtained by scanning the building surface of the target building through a measuring instrument. In actual operation, the measuring instrument can be selected according to actual conditions. For example, the first point cloud data may be obtained by scanning the building surface with a measuring instrument such as a laser scanner, a stereo camera, or a transit time camera.
In a preferred embodiment of the present application, the measuring device may be an industrial-grade laser scanner. In the scanning process, the industrial-grade laser scanner may select any point having a distance greater than a preset distance from the building surface as a reference point based on the ground, scan the building surface in a scanning field range of 360 ° x 270 °, and send the scanned first point cloud data to the terminal. And after the terminal acquires the first point cloud data, processing the first point cloud data.
And 102, restoring the first point cloud image of the building surface according to the first point cloud data.
The first cloud image is an image of an architectural surface of the target building. After the first point cloud data is acquired, the terminal can restore the first point cloud image of the building surface in different modes.
In some embodiments of the present application, the three-dimensional coordinate data of each point may be included in the first point cloud data obtained by scanning the building surface by the measuring instrument. At this time, the terminal may acquire three-dimensional coordinate data of the first point cloud data, and restore the first point cloud image of the building surface according to the three-dimensional coordinate data.
In the three-dimensional coordinate data, the coordinate axis for representing the coordinate may be a point where the X value, the Y value, and the Z value in the coordinate are all infinite, for example, a laser beam emitting position of an industrial-grade laser scanner is used as a coordinate far end; the Z axis is positioned in the vertical scanning plane and is positive upwards; the X axis is positioned in the transverse scanning plane, is vertical to the Z axis and is vertical to the direction of the building surface; the Y axis is located within the transverse scan plane and perpendicular to the X axis and forms a right hand coordinate system with the X axis and the Z axis, with the positive Y axis direction pointing toward the building surface.
Wherein, the standard color block refers to the color data meeting the color requirement of the building surface. The acquisition mode of the standard color blocks can be selected by an administrator according to actual conditions. For example, color data of a standard patch may be input by an administrator, generating a standard patch; or, any area in the first point cloud image is used as a standard color block.
As a preferred embodiment of the present application, the standard color blocks may be obtained by performing data analysis on historical standard color block data to generate a standard color block set, and obtaining preset standard color blocks in the standard color block set. For example, when the color difference detection is performed on the fair-faced concrete external wall panel, a standard color block set can be generated by acquiring historical data of standard color blocks of the fair-faced concrete external wall panel, and then one standard color block is selected from the standard color block set to serve as the standard color block.
As another preferred embodiment of the present application, the standard color blocks may be obtained by selecting the standard color blocks from the first cloud image through a preset algorithm. For example, the RGB average value of the first point cloud image may be calculated, and a region closest to the RGB average value in the first point cloud image may be set as a standard color patch.
In the embodiment of the application, after the first point cloud image on the building surface is restored, a preset standard color block may be obtained, and the first point cloud image is subjected to color difference detection by using the standard color block, so as to obtain a first color difference detection result representing a color difference between the first point cloud image and the standard color block.
It should be noted that the standard color block may be an image, or may be an attribute value representing a color, such as an RGB value. If the standard color block is an image, the first point cloud image and the standard color block can be directly subjected to color comparison to obtain a first color difference detection result. If the standard color block is an attribute value representing color, the attribute value of the first point cloud image needs to be compared with the attribute value of the standard color block to obtain a first color difference detection result.
In the embodiment of the application, the first point cloud image of the building surface is restored by acquiring the first point cloud data of the building surface and according to the first point cloud data. At this time, a preset standard color block may be obtained, and the first cloud image is subjected to color difference detection by using the standard color block, so as to obtain a first color difference detection result. The embodiment of the application realizes the color difference detection of the building surface, and the color difference detection result is obtained by comparing the color difference of the first point cloud image with the preset standard color block instead of judging the color difference through human eyes, so that the influence of individual subjectivity is avoided, the reliability and traceability of the color difference detection result are improved, and the efficiency is higher compared with the existing artificial color difference detection mode.
In practical applications, for example, when performing color difference detection on the fair-faced concrete external wall panel, it is often required that the color difference of each region of the fair-faced concrete external wall panel is not too large. Therefore, in some embodiments of the present application, before step 103, the method may include: and carrying out image segmentation processing on the first point cloud image to obtain a plurality of image areas.
The mode of the image segmentation processing can be selected according to actual situations. The image segmentation may be performed according to the structure of the building surface, for example, by segmenting different portions such as doors, windows, and exterior walls as different image areas. Specifically, after the first point cloud image is restored, the first point cloud image may be subjected to image recognition, different decoration surface types are recognized, and corresponding regions of the decoration surfaces of the same type in the first point cloud image in the different decoration types are divided into the same image region.
In some embodiments of the present application, the image segmentation may also be performed in an equal segmentation manner.
Specifically, since it is often necessary to perform rework processing on the corresponding area on the building surface of the image area with the unqualified color after obtaining the first color difference detection result, in some embodiments of the present application, as shown in fig. 2, the image segmentation process may include the following steps 201 to 202.
Wherein the preset area value is the minimum reworking area value of the building surface of the target building. The minimum rework area value is the minimum area value that a factory can produce each time when producing surfacing materials (such as exterior walls, doors and windows) used to construct building surfaces. For example, the area value corresponding to the smallest wallboard that can be produced by a factory when producing wallboard.
And the area value of the image area is greater than or equal to the minimum rework area value.
That is, the terminal divides the area of the image area into a plurality of image areas having an area size greater than or equal to the minimum rework area value, so that when performing rework processing on the area corresponding to the image area with the unqualified color on the building surface, no other operations such as cutting, cropping and the like are required. Thereby avoiding waste, saving working procedures and achieving the effects of improving efficiency and reducing cost.
The size of the image area may be set to other values, for example, the size of the image area may be set to an image area having an area size of 50 decimeters × 50 decimeters, and may be specifically set according to actual needs of an administrator. The smaller the area size of the image area, the more image areas may need to be reworked, but the more desirable, e.g., more uniform, color of the resulting architectural surface. The larger the area size of the image area is, the less image areas need to be reworked, and the efficiency of the whole industrial processing flow is higher.
In other embodiments of the present application, different portions such as a door, a window, an outer wall, and the like may be divided into different image areas, so that when the color difference of the image areas does not meet the requirement, rework processing may be performed on a targeted basis. For example, when the image area corresponding to the window does not meet the requirement, the window is directly reworked.
Correspondingly, after the image segmentation processing is completed, the performing, by using the standard color block, color difference detection on the first dot cloud image to obtain a first color difference detection result may include: and respectively carrying out color difference detection on each image area by using the standard color blocks to obtain a first color difference detection result.
That is, after obtaining a plurality of image regions, color difference detection may be performed on each image region using the standard patch, and a first color difference detection result indicating a color difference between each image region and the standard patch may be obtained.
In some embodiments of the present application, any image region may be directly selected as a standard color block, and other image regions in the plurality of image regions may be compared with the image region selected as the standard color block to obtain a first color difference detection result.
For example, as shown in fig. 3, after the first point cloud data of the building surface is acquired, the first point cloud image 31 of the building surface may be restored, and the first point cloud image 31 may be divided into 12 image areas, at this time, the image area 301 may be selected as a standard color block, and the other image areas in the plurality of image areas may be compared with the image area 301 to obtain a first color difference detection result.
Specifically, as shown in fig. 4, in the process of performing color difference detection on the first cloud image by using the standard color block to obtain a first color difference detection result, the operation on a single image region may include the following steps 401 to 402.
In some embodiments of the present application, the RGB value data of each point may be included in the first point cloud data obtained by scanning the building surface by the surveying instrument. The terminal can obtain RGB value data of the first point cloud data, determine the RGB value of each pixel point in the first point cloud image according to the RGB value data, and further calculate the average value of the RGB values of all the pixel points in the image area after finishing image segmentation processing to obtain the first RGB average value.
That is, after obtaining a plurality of image regions, the first RGB average value of each image region may be compared with the RGB values of the standard color patches to obtain a comparison result of color differences between each image region and the standard color patches, and further obtain a first color difference detection result.
In practical application, the first RGB average value of each image area is hardly consistent with the RGB value of the standard color patch, that is, in the process of comparing the first RGB average value with the RGB value of the standard color patch, if all image areas with different first RGB average values and RGB values of the standard color patches are required to be reworked in the associated area in the building surface, the problems of large engineering quantity and low efficiency may be caused. In order to solve this problem, the first color difference detection result of the image area closer to the standard color block may be determined as qualified color difference.
Specifically, as shown in fig. 5, the comparing the first RGB average value with the RGB value of the standard color patch to obtain the first color difference detection result of the image area may include the following steps 501 to 503.
Wherein the preset color difference threshold represents the maximum allowable RGB difference between the first RGB average value of the image area and the RGB value of the standard color block. It should be noted that the preset color difference threshold may be adjusted according to actual situations.
In some embodiments of the application, if the comparison result is that the difference between the first RGB average value and the RGB value of the standard color block is greater than the preset color difference threshold, which indicates that the color difference between the image region and the standard color block exceeds the allowable range, it may be determined that the first color difference detection result of the image region is a color difference failure.
In step 503, if the comparison result is that the difference between the first RGB average value and the RGB value of the standard color patch is less than or equal to a preset color difference threshold, it is determined that the first color difference detection result of the image area is qualified.
In some embodiments of the application, if the comparison result is that the difference between the first RGB average value and the RGB value of the standard color block is less than or equal to the preset color difference threshold, which indicates that the color difference between the image region and the standard color block is within the allowable range, it may be determined that the first color difference detection result of the image region is qualified.
For example, as shown in fig. 3, after the first point cloud image 31 of the building surface is divided into 12 image areas and the image area 301 is selected as a standard patch, other image areas of the plurality of image areas may be compared with the image area 301. Since the first RGB average value of the image area 301 is (191, 191, 191), the first RGB average value of the image area 302 is (191, 191, 191), the first RGB average value of the image area 303 is (216, 216, 216), and the preset color difference threshold value is 20 for each channel value of RGB. Therefore, the difference between the first RGB average value of the image area 302 and the RGB value of the standard color patch (i.e. the first RGB average value of the image area 301) is smaller than the preset color difference threshold, and the first color difference detection result of the image area 302 is determined to be qualified for color difference. The difference between the first RGB average value of the image area 303 and the RGB value of the standard color patch (i.e. the first RGB average value of the image area 301) is greater than the preset color difference threshold, and it is determined that the first color difference detection result of the image area 303 is a color difference failure.
It can be understood that when the first color difference detection result of the image area is that the color difference is not qualified, the image area with the unqualified color difference needs to be reworked in the area associated with the building surface, so that the building surface of the target building meets the color requirement.
Specifically, as shown in fig. 6, the color difference detection method further includes the following steps 601 to 604.
That is, the target image area is an image area whose first color difference detection result is that the color difference is not qualified.
The preset updating condition is triggered when the image area with unqualified color difference finishes reworking.
Specifically, the present application does not excessively limit the triggering manner of the preset update condition. The terminal triggers a preset updating condition when receiving a color difference detection instruction input by an administrator; or, the terminal monitors the building surface in real time and triggers a preset updating condition when detecting that the building surface is updated.
The building sub-area is an area where the target image area is associated in a building surface.
When the preset updating condition is triggered, which indicates that the image area with unqualified color difference has completed reworking in the building sub-area associated with the building surface, at this time, the color difference between the building sub-area and the standard color block needs to be detected again. Therefore, a second point cloud image of the building sub-region needs to be acquired.
Specifically, the obtaining manner of the second point cloud image may refer to the above steps 101 to 102, which is not described herein again.
And step 604, performing color difference detection on the second point cloud image by using the standard color block to obtain a second color difference detection result.
That is to say, after obtaining the plurality of image areas, after reworking the building sub-area with the original color difference being unqualified, the color difference detection may be performed on the second point cloud image of the reworked building sub-area by using the standard color block, so as to obtain a second color difference detection result of the color difference between the area and the standard color block.
In the embodiment of the application, when the preset updating condition is triggered, a second point cloud image of the building subregion is obtained, the second point cloud image is compared with the standard color block in color to obtain a second color difference detection result, and whether the color of the building subregion after reworking meets the requirement is further judged. It can be understood that if the second color difference detection result is that the color difference is qualified, the color of the reworked building sub-area meets the requirement; and if the second color difference detection result is that the color difference is unqualified, continuing reworking until the color of the building subarea meets the requirement.
In addition, in some embodiments of the application, when the first color difference detection result or the second color difference detection result is obtained, a point cloud color difference identification report can be generated, so that a worker can conveniently look up the color difference detection result in time, and the traceability of the color difference detection method is improved.
In practice, the outer surface of the architectural surface is often not monochromatic, i.e. different areas of the architectural surface of the target building have different colors; for example, as shown in FIG. 7, different areas of the architectural surface 71 of the target building are different colors. In this case, it is necessary to detect the color difference for each region.
Specifically, as shown in fig. 8, the obtaining of the preset standard color block on the building surface and performing color difference detection on each image region by using the standard color block to obtain the first color difference detection result may include the following steps 801 to 802.
That is, each image region has a standard patch corresponding thereto. Correspondingly, the standard color blocks can be obtained by respectively inputting the color data of each standard color block by an administrator and generating each standard color block; alternatively, the standard color blocks corresponding to the respective image areas can be determined by a prefabricated color image of the building surface (e.g., a color design drawing of the building surface).
And step 802, performing color difference detection on the image area corresponding to the standard color block by using the standard color block to obtain a first color difference detection result.
That is to say, each image area is compared with the standard color block corresponding to the image area, and whether each image area meets the color requirement can be determined, so as to obtain the first color difference detection result.
For example, as shown in fig. 7, color comparison is performed on an image region 701 of the first cloud image 71 on the building surface and a standard patch 704 corresponding to the image region, color comparison is performed on an image region 702 and a standard patch 705 corresponding to the image region, and color comparison is performed on an image region 703 and a standard patch 706 corresponding to the image region, so that whether the image regions 701, 702, and 703 meet the color requirement can be determined, and a first color difference detection result can be obtained.
In some embodiments of the present application, if the image area is divided according to different types of decoration surfaces, the standard color blocks correspond to the different types of decoration surfaces one to one. For example, the image region representing the door may correspond to a standard patch; the image area representing the wall surface may correspond to another standard color patch.
Further, in practical applications, the same decorative category may have multiple colors, for example, windows on the same building surface may have different colors. Correspondingly, the number of standard color blocks corresponding to the image area representing a certain decorative surface category is also multiple. In this case, performing color difference detection on the image region may include: and comparing the image area with a plurality of standard color blocks corresponding to the image area respectively to obtain a first color difference detection result. In the first color difference detection result, if the color difference between the image area and any one of the plurality of standard color patches corresponding to the image area is smaller than a preset color difference threshold, it indicates that the image area meets the color difference requirement.
In the embodiment of the application, the standard color blocks corresponding to the image areas one to one are obtained, and the image areas corresponding to the standard color blocks are subjected to color difference detection by using the standard color blocks to obtain a first color difference detection result, so that the color difference detection of the surface of a multicolor building is realized, and the practicability of the color difference detection method is improved.
It should be noted that, for simplicity of description, the foregoing method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts, as some steps may, in accordance with the present application, occur in other orders.
As shown in fig. 9, a schematic structural diagram of a color difference detection apparatus 900 based on a point cloud technology according to an embodiment of the present disclosure is provided, where the color difference detection apparatus 900 based on the point cloud technology is configured on a terminal, and the color difference detection apparatus 900 based on the point cloud technology may include: a data acquisition unit 901, a data processing unit 902, and a color difference detection unit 903.
A data acquiring unit 901, configured to acquire first point cloud data of a building surface;
the data processing unit 902 is configured to restore a first point cloud image of the building surface according to the first point cloud data;
the color difference detection unit 903 is configured to obtain a preset standard color block, and perform color difference detection on the first cloud image by using the standard color block to obtain a first color difference detection result.
In some embodiments of the present application, the data processing unit 902 is further specifically configured to: and acquiring three-dimensional coordinate data of the first point cloud data, and restoring the first point cloud image of the building surface according to the three-dimensional coordinate data.
In some embodiments of the present application, the color difference detection apparatus 900 based on the point cloud technology further includes an image segmentation unit, which performs image segmentation on the first point cloud image to obtain a plurality of image regions; the data processing unit 902 is further specifically configured to: and respectively carrying out color difference detection on each image area by using the standard color blocks to obtain the first color difference detection result.
In some embodiments of the present application, the image segmentation unit is further specifically configured to: acquiring a preset area value; the preset area value is a minimum rework area value of the outer surface of the building surface; performing image segmentation processing on the first point cloud image to obtain a plurality of image areas; the area value of the image region is greater than or equal to the minimum rework area value.
In some embodiments of the present application, the color difference detection unit 903 is further specifically configured to: if the first color difference detection result of any one of the image areas is unqualified, taking the image area as a target image area; detecting whether a preset updating condition is triggered or not; if the preset updating condition is triggered, acquiring a second point cloud image of a building subregion, wherein the building subregion is a region associated with a target image region in the building surface; and carrying out color difference detection on the second point cloud image by using the standard color block to obtain a second color difference detection result.
In some embodiments of the present application, the color difference detection unit 903 is further specifically configured to: acquiring the standard color blocks which correspond to the image areas one by one; and carrying out color difference detection on the image area corresponding to the standard color block by using the standard color block to obtain a first color difference detection result.
In some embodiments of the present application, the color difference detection unit 903 is further specifically configured to: acquiring a first RGB average value of all pixel points in the image area; and comparing the first RGB average value with the RGB value of the standard color block to obtain the first color difference detection result of the image area.
In some embodiments of the present application, the color difference detection unit 903 is further specifically configured to: acquiring a preset color difference threshold; if the comparison result is that the difference value between the first RGB average value and the RGB value of the standard color block is larger than the preset color difference threshold value, determining that the first color difference detection result of the image area is unqualified in color difference; and if the comparison result is that the difference value between the first RGB average value and the RGB value of the standard color block is smaller than or equal to the preset color difference threshold value, judging that the first color difference detection result of the image area is qualified in color difference.
It should be noted that, for convenience and simplicity of description, the specific working process of the color difference detection apparatus 900 based on the point cloud technology may refer to the corresponding process of the method described in fig. 1 to fig. 8, and is not described herein again.
Fig. 10 is a schematic diagram of a terminal according to an embodiment of the present application. The terminal 100 may include: a processor 1000, a memory 1001 and a computer program 1002 stored in said memory 1001 and executable on said processor 1000, such as a color difference detection device program based on point cloud technology. The processor 1000, when executing the computer program 1002, implements the steps in each of the above-described embodiments of the color difference detection method, such as the steps 101 to 103 shown in fig. 1. Alternatively, the processor 1000, when executing the computer program 1002, implements the functions of each module/unit in each device embodiment described above, for example, the functions of the units 901 to 903 shown in fig. 9.
The computer program may be partitioned into one or more modules/units that are stored in the memory 1001 and executed by the processor 1000 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program in the terminal. For example, the computer program may be divided into a data acquisition unit, a data processing unit, and a color difference detection unit, each unit functioning specifically as follows:
the data acquisition unit is used for acquiring first point cloud data of the surface of the building;
the data processing unit is used for restoring a first point cloud image of the building surface according to the first point cloud data;
and the color difference detection unit is used for acquiring a preset standard color block and carrying out color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result.
The terminal can be a computing device such as a smart phone, a desktop computer, a notebook computer, a palm computer and a cloud server. The terminal may include, but is not limited to, a processor 1000, a memory 1001. Those skilled in the art will appreciate that fig. 10 is merely an example of a terminal and is not intended to be limiting and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., the terminal may also include input-output devices, network access devices, buses, etc.
The Processor 1000 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 1001 may be an internal storage unit of the terminal, such as a hard disk or a memory of the terminal. The memory 1001 may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal. Further, the memory 1001 may also include both an internal storage unit and an external storage device of the terminal. The memory 1001 is used for storing the computer program and other programs and data required by the terminal. The memory 1001 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (9)
1. A color difference detection method based on a point cloud technology is characterized by comprising the following steps:
acquiring first point cloud data of the surface of a building;
restoring a first point cloud image of the building surface according to the first point cloud data;
acquiring a preset standard color block, and performing color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result;
before the performing color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result, the method comprises the following steps:
performing image segmentation processing on the first point cloud image to obtain a plurality of image areas;
the image segmentation processing on the first point cloud image to obtain a plurality of image areas comprises:
carrying out image recognition on the first cloud point image, and recognizing a decorative surface and a decorative surface type to which the decorative surface belongs;
dividing the corresponding areas of the decorative surfaces of the same decorative surface type in the first point cloud image into the same image area;
correspondingly, the performing color difference detection on the first point cloud image by using the standard color block to obtain a first color difference detection result, including:
and respectively carrying out color difference detection on each image area by using the standard color blocks to obtain the first color difference detection result.
2. The method for detecting chromatic aberration according to claim 1, wherein the restoring the first point cloud image of the building surface according to the first point cloud data includes:
and acquiring three-dimensional coordinate data of the first point cloud data, and restoring the first point cloud image of the building surface according to the three-dimensional coordinate data.
3. The method of detecting color difference according to claim 1, wherein the performing image segmentation processing on the first point cloud image to obtain a plurality of image regions comprises:
acquiring a preset area value; the preset area value is the minimum reworking area value of the building surface;
performing image segmentation processing on the first point cloud image to obtain a plurality of image areas; the area value of the image region is greater than or equal to the minimum rework area value.
4. The color difference detection method according to claim 1 or 3, characterized by further comprising:
if the first color difference detection result of any one of the image areas is unqualified in color difference, taking the image area as a target image area;
detecting whether a preset updating condition is triggered or not;
if the preset updating condition is triggered, acquiring a second point cloud image of a building subarea, wherein the building subarea is an area related to the target image area in the building surface;
and carrying out color difference detection on the second point cloud image by using the standard color block to obtain a second color difference detection result.
5. The method of claim 1 or 3, wherein the obtaining a predetermined standard color block and performing color difference detection on each image region by using the standard color block to obtain the first color difference detection result comprises:
acquiring the standard color blocks which correspond to the image areas one by one;
and carrying out color difference detection on the image area corresponding to the standard color block by using the standard color block to obtain a first color difference detection result.
6. The method as claimed in claim 1 or 3, wherein the operation on a single image region in the process of obtaining the first color difference detection result by performing color difference detection on each image region by using the standard color block comprises:
acquiring a first RGB average value of all pixel points in the image area;
and comparing the first RGB average value with the RGB value of the standard color block to obtain the first color difference detection result of the image area.
7. The method of claim 6, wherein comparing the first RGB average value with the RGB values of the standard color patch to obtain the first color difference detection result of the image area comprises:
acquiring a preset color difference threshold;
if the comparison result is that the difference value between the first RGB average value and the RGB value of the standard color block is larger than the preset color difference threshold value, determining that the first color difference detection result of the image area is unqualified in color difference;
and if the comparison result is that the difference value between the first RGB average value and the RGB value of the standard color block is smaller than or equal to the preset color difference threshold value, judging that the first color difference detection result of the image area is qualified in color difference.
8. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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